English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 49064/83170 (59%)
造访人次 : 6963022      在线人数 : 53
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜寻范围 查询小技巧:
  • 您可在西文检索词汇前后加上"双引号",以获取较精准的检索结果
  • 若欲以作者姓名搜寻,建议至进阶搜寻限定作者字段,可获得较完整数据
  • 进阶搜寻

    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/97466

    题名: Data Mining Based Intelligent System for Voting Behavior Analysis
    作者: Chen, Duen-Kai
    贡献者: 淡江大學資訊創新與科技學系
    关键词: Data Mining(DM);Voting Behavior Analysis;TEDS
    日期: 2013-01
    上传时间: 2014-03-20 14:03:22 (UTC+8)
    出版者: Stafa-Zurich: Trans Tech Publications Ltd.
    摘要: In this study, we report a voting behavior analysis intelligent system based on data mining technology. From previous literature, we have witnessed increasing number of studies applied information technology to facilitate voting behavior analysis. In this study, we built a likely voter identification model through the use of data mining technology, the classification algorithm used here constructs decision tree model to identify voters and non voters. This model is evaluated by its accuracy and number of attributes used to correctly identify likely voter. Our goal is to try to use just a small number of survey questions while maintaining the accuracy rates of other similar models. This model was built and tested on Taiwan’s Election and Democratization Study (TEDS) data sets. According to the experimental results, the proposed model can improve likely voter identification rate and this finding is consistent with previous studies based on American National Election Studies.
    關聯: Applied Mechanics and Materials 284-287, pp.3070-3073
    DOI: 10.4028/www.scientific.net/AMM.284-287.3070
    显示于类别:[資訊創新與科技學系] 期刊論文


    档案 描述 大小格式浏览次数



    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回馈